Spatial regression models with compositional responses using the \(\alpha\)--transformation. The models includes are the \(\alpha\)-regression (not spatial), the \(\alpha\)-spatially lagged X (\(\alpha\)-SLX) model and the geographically weighted \(\alpha\)-regression (GW\(\alpha\)R) model.
Michail Tsagris mtsagris@uoc.gr.
Michail Tsagris <mtsagris@uoc.gr>
| Package: | CompositionalSR |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2025-10-17 |
| License: | GPL-2 |
Tsagris M. (2025). The \(\alpha\)--regression for compositional data: a unified framework for standard, spatially-lagged, and geographically-weighted regression models. https://arxiv.org/pdf/2510.12663
Tsagris M. (2015). Regression analysis with compositional data containing zero values. Chilean Journal of Statistics, 6(2): 47-57. https://arxiv.org/pdf/1508.01913v1.pdf
Tsagris M.T., Preston S. and Wood A.T.A. (2011). A data-based power transformation for compositional data. In Proceedings of the 4th Compositional Data Analysis Workshop, Girona, Spain. https://arxiv.org/pdf/1106.1451.pdf